The present invention relates generally to the field of knowledge management, and more particularly to acquiring and transferring tacit knowledge between users.
Knowledge management refers to a multi-disciplined approach encompassing the process of capturing, developing, sharing, and effectively using knowledge to achieve organizational objectives (e.g., improved performance, competitive advantage, innovation, sharing of lessons learned, integration, and continuous improvement). Knowledge is a familiarity, awareness, or understanding of someone or something acquired through experience or education (e.g., facts, information, descriptions, or skills). Knowledge may be broken into two categories, explicit and tacit. Explicit knowledge is knowledge that has been articulated, codified, and stored in certain media and can be easily conveyed to others (e.g., information contained in encyclopedias and textbooks). Tacit knowledge, however, is knowledge that people are not often consciously aware of (e.g., how to perform a particular task) and is difficult to convey to others through writing or verbalizing.
When individuals utilize computers and the Internet, digital footprints (e.g., digital shadows) are created. Digital footprints refer to the trails or traces of information left behind in a digital environment (e.g., forum registrations, e-mails, uploads, images, activity, etc.), which may be stored as cookies (i.e., small pieces of data sent from a website and stored in the browser of the user tracking online activity). Digital footprints also reside within computer memory as files, indicating actions performed on a computing device (e.g., performed actions, data accessed, programs utilized, etc.). Based on the digital footprints, knowledge about the individual and the information which may have been accessed and/or created by the user may be discerned through data collection techniques and analyses, such as spider programs, text analytics, and data mining gather knowledge (e.g., gather explicit or tacit knowledge).
Spider programs are software programs or automated scripts that travel the Web, locating data and indexing information that are also capable of extracting information (e.g., e-mail addresses, search information, frequency) associated with an individual (e.g., user). Text analytics (e.g., text mining) refers to the process of deriving high quality information (e.g., relevant and novel) from text by discerning patterns and trends within the structure of the input text (e.g., utilizes parsing and derived linguistic features). Data mining discovers patterns in large data sets, including: associations (e.g., relationships between variables), clustering (e.g., similar groups and structures), and classification (e.g., applying a known structure to new data), and summarization (e.g., compact representation of the data set).